arXiv subjects

Maxwell G. A. Maltz

Publications and source records attributed to Maxwell G. A. Maltz.

4 recordsLinked to original sources

arXiv2025

First Light And Reionisation Epoch Simulations (FLARES) XX: Comparing semi-analytic models at high-redshift

We explore how the choice of galaxy formation model affects the predicted properties of high-redshift galaxies. Using the FLARES zoom resimulation strategy, we compare the EAGLE hydrodynamics model and the GALFORM, L-Galaxies, SC-SAM and SHARK semi-analytic models (SAMs) at $5\leq z \leq 12$. The first part of our analysis examines the stellar mass functions, stellar-to-halo mass relations, star formation rates, and supermassive black hole (SMBH) properties predicted by the different models. Comparisons are made with observations, where relevant. We find general agreement between the range of predicted and observed stellar mass functions. The model predictions differ considerably when it comes to SMBH properties, with GALFORM and SHARK predicting between 1.5-3 dex more massive SMBHs ($M_{\rm BH}>10^6\ {\rm M_\odot}$) than L-Galaxies and SC-SAM, depending on redshift. The second half of our analysis focuses on passive galaxies. We show that in L-Galaxies and SC-SAM, environmental quenching of satellites is the prevalent quenching mechanism, with active galactic nuclei (AGN) feedback having little effect at the redshifts probed. On the other hand, $\sim40\%$ of passive galaxies predicted by GALFORM and SHARK are quenched by AGN feedback at $z=5$. The SAMs are an interesting contrast to the EAGLE model, in which AGN feedback is essential for the formation of passive galaxies, in both satellites and centrals, even at high redshift.

astro-ph.GA↗

arXiv2025

First Light And Reionization Epoch Simulations (FLARES) -- XIX: Supermassive black hole mergers in the early Universe and their environmental dependence

The upcoming space-based gravitational wave (GW) observatory, LISA, is expected to detect GW signals from supermassive black hole (SMBH) mergers occurring at high redshifts. However, understanding the origin and growth of SMBHs in the early Universe remains an open problem in astrophysics. In this work, we utilize the First Light And Reionization Epoch Simulations (FLARES), a suite of cosmological hydrodynamical zoom-in simulations, to study SMBH mergers at $5 \lesssim z \lesssim 10$ across a wide range of environments. Most mergers in FLARES involve secondary SMBHs near the seed mass ($m_{\rm seed} \approx 1.5 \times 10^{5}~{\rm M}_{\odot}$) while primary SMBHs span up to $10^{9}~{\rm M}_{\odot}$, resulting in mass ratios from $q \sim 10^{-4}$ to $1$, with a peak at $q \sim 1$. The number of mergers increases rapidly towards lower redshifts, and the comoving total number density scales with overdensity as $n_{\rm merger} = 10^{-3.81} (1 + δ)^{4.78}$. Denser regions host more massive mergers, with higher merger redshifts and lower mass ratios. Within the FLARES redshift range, LISA is expected to detect mergers with $10^{5} \lesssim M_{\rm tot}/{\rm M}_{\odot} \lesssim 10^{8}$ and $q \gtrsim 10^{-2}$, corresponding to a detection rate of $0.030~{\rm yr}^{-1}$ for events with signal-to-noise ratio ${\rm SNR} \geq 10$. Our study demonstrates the sensitivity of GW predictions at high redshifts to SMBH seed models and merger time delays, highlighting the need for improved modeling in future cosmological simulations to maximize LISA's scientific return.

astro-ph.GA↗

arXiv2024

First Light and Reionisation Epoch Simulations (FLARES) XVII: Learning the galaxy-halo connection at high redshifts

Understanding the galaxy-halo relationship is not only key for elucidating the interplay between baryonic and dark matter, it is essential for creating large mock galaxy catalogues from N-body simulations. High-resolution hydrodynamical simulations are limited to small volumes by their large computational demands, hindering their use for comparisons with wide-field observational surveys. We overcome this limitation by using the First Light and Reionisation Epoch Simulations (FLARES), a suite of high-resolution (M_gas = 1.8 x 10^6 M_Sun) zoom simulations drawn from a large, (3.2 cGpc)^3 box. We use an extremely randomised trees machine learning approach to model the relationship between galaxies and their subhaloes in a wide range of environments. This allows us to build mock catalogues with dynamic ranges that surpass those obtainable through periodic simulations. The low cost of the zoom simulations facilitates multiple runs of the same regions, differing only in the random number seed of the subgrid models; changing this seed introduces a butterfly effect, leading to random differences in the properties of matching galaxies. This randomness cannot be learnt by a deterministic machine learning model, but by sampling the noise and adding it post-facto to our predictions, we are able to recover the distributions of the galaxy properties we predict (stellar mass, star formation rate, metallicity, and size) remarkably well. We also explore the resolution-dependence of our models' performances and find minimal depreciation down to particle resolutions of order M_DM ~ 10^8 M_Sun, enabling the future application of our models to large dark matter-only boxes.

astro-ph.GA↗

arXiv2023

First Light and Reionisation Epoch Simulations (FLARES) X: Environmental Galaxy Bias and Survey Variance at High Redshift

Upcoming deep galaxy surveys with JWST will probe galaxy evolution during the epoch of reionisation (EoR, $5\leq z\leq10$) over relatively compact areas (e.g. $\sim$ 300\,arcmin$^2$ for the JADES GTO survey). It is therefore imperative that we understand the degree of survey variance, to evaluate how representative the galaxy populations in these studies will be. We use the First Light And Reionisation Epoch Simulations (FLARES) to measure the galaxy bias of various tracers over an unprecedentedly large range in overdensity for a hydrodynamic simulation, and use these relations to assess the impact of bias and clustering on survey variance in the EoR. Star formation is highly biased relative to the underlying dark matter distribution, with the mean ratio of the stellar to dark matter density varying by a factor of 100 between regions of low and high matter overdensity (smoothed on a scale of 14$\,h^{-1}$cMpc). This is reflected in the galaxy distribution --the most massive galaxies are found solely in regions of high overdensity. As a consequence of the above, galaxies in the EoR are highly clustered, which can lead to large variance in survey number counts. For mean number counts $N\lesssim 100$ (1000), in a unit redshift slice of angular area 300\,arcmin$^2$ (1.4\,deg$^2$), the 2-sigma range in $N$ is roughly a factor of four (two). We present relations between the expected variance and survey area for different survey geometries; these relations will be of use to observers wishing to understand the impact of survey variance on their results.

astro-ph.GA↗